Linear Algebra for Machine Learning

Machine Learning is at the forefront of Data Science and analytical coding, but to fully appreciate machine learning, one must have an understanding of the underlying math and statistics involved. The course will introduce you to the linear algebra concepts involved in understanding and implementing machine learning algorithms, as well as in their derivation.

This class will cover topics including:

• Matrices
• Types of matrix
• Matrix transposition
  
• Matrix multiplication
• Matrix inversion
• Eigen values
• Eigen vectors
• Matrix transformation

This class is meant for those without any particular coding background, though some mathematical background will be helpful. Attendees will do best having taken algebra at some point, as those are the concepts that we will build upon.